Neutrophil migration induced by IL-1 beta depends upon LTB4 released by macrophages and upon TNF-alpha and IL-1 beta released by mast cells

In the present study, we investigate whether mast cells and macrophages are involved in the control of IL-1 beta-induced neutrophil migration, as well as the participation of chemotactic mediators. IL-1 beta induced a dose-dependent neutrophil migration to the peritoneal cavity of rats which depends on LTB4, PAF and cytokines, since the animal treatment with inhibitors of these mediators (MK 886, PCA 4248 and dexamethasone respectively) inhibited IL-1 beta-induced neutrophil migration. The neutrophil migration induced by IL-1 beta is dependent on mast cells and macrophages, since depletion of mast cells reduced the process whereas the increase of macrophage population enhanced the migration. Moreover, mast cells or macrophages stimulated with IL-1 beta released a neutrophil chemotactic factor, which mimicked the neutrophil migration induced by IL-1 beta. The chemotactic activity of the supernatant of IL-1 beta-stimulated macrophages is due to the presence of LTB4, since MK 886 inhibited its release. Moreover, the chemotactic activity of IL-1 beta-stimulated mast cells supernatant is due to the presence of IL-1 beta and TNF-alpha, since antibodies against these cytokines inhibited its activity. Furthermore, significant amounts of these cytokines were detected in the supernatant. In conclusion, our results suggest that neutrophil migration induced by IL-1 beta depends upon LTB4 released by macrophages and upon IL-1 beta and TNF alpha released by mast cells.

Vascular permeability, neutrophil migration and edematogenic effects induced by the latex of Cryptostegia grandiflora

Inflammatory responses have been described as occurring after exposure to some latex materials. In this study pro-inflammatory activity in the latex of Cryptostegia grandiflora was investigated. The soluble proteins of the latex (CgLP) were isolated from the whole latex and evaluated by in vivo assays. CgLP induced strong inflammatory activity mediated by neutrophil migration, enlarging vascular permeability and increasing myeloperoxidase activity locally in rats. CgLP-induced inflammation was observed in peritonitis, paw edema and air push models. In addition, CgLP caused hyperemia in a healing model. The peritonitis effect was lost when CgLP was previously boiled suggesting the involvement of proinflammatory proteins. Thioglycollate increased the neutrophil migration induced by CgLP, but not by fMLP Mast cell depletion provoked by 40/80 compound did not modify the course of inflammation triggered by CgLP, being similar to fMLP, which suggested that neutrophil migration was induced by direct mechanism mediated by macrophages. Neutrophil migration stimulated by CgLP was strongly inhibited by Dexamethasone and to a lesser extent by Thalidomide, indicating the involvement of cytokines in mediating neutrophil infiltration. Celecoxib and Indomethacin were inhibitory suggesting the involvement of prostaglandins. Cimetidine was effective only in the initial phase of edema. PCA 4248 was ineffective. It is concluded that the latex of C. grandiflora is a potent inflammatory fluid, and also that laticifer proteins may be implicated in this process. (c) 2008 Elsevier Ltd. All rights reserved.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Ecological niche modeling and principal component analysis of Krameria Loefl. (Krameriaceae)

Krameria plants are found in arid regions of the Americas and present a floral system that attracts oil-collecting bees. Niche modeling and multivariate tools were applied to examine ecological and geographical aspects of the 18 species of this genus, using occurrence data obtained from herbaria and literature. Niche modeling showed the potential areas of occurrence for each species and the analysis of climatic variables suggested that North American species occur mostly in deserted or xeric ecoregions with monthly precipitation below 140 mm and large temperature ranges. South American species are mainly found in deserted ecoregions and subtropical savannas where monthly precipitation often exceeds 150 mm and temperature ranges are smaller. Principal Component Analysis (PCA) performed with values of temperature and precipitation showed that the distribution limits of Krameria species are primarily associated with maximum and minimum temperatures. Modeling of Krameria species proved to be a useful tool for analyzing the influence of the ecological niche variables in the geographical distribution of species, providing new information to guide future investigations. (C) 2011 Elsevier Ltd. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

Development and Validation of a Mice liar Electrokinetic Chromatography Method for Quantitative Determination of Butenolides in Piper malacophyllum (C. Presl) C. DC.

Introduction - A large number of natural and synthetic compounds having butenolides as a core unit have been described and many of them display a wide range of biological activities. Butenolides from P. malacophyllum have presented potential antifungal activities but no specific, fast, and precise method has been developed for their determination. Objective - To develop a methodology based on micellar electrokinetic chromatography to determine butenolides in Piper species. Methodology - The extracts were analysed in an uncoated fused-silica capillaries and for the micellar system 20 mmol/L SDS, 20% (v/v) acetonitrile (ACN) and 10 mmol/L STB aqueous buffer at pH 9.2 were used. The method was validated for precision, linearity, limit of detection (LOD) and limit of quantitation (LOQ) and the standard deviations were determined from the standard errors estimated by the regression line. Results - A micellar electrokinetic chromatography (MEKC) method for determination of butenolides in extracts gave full resolution for 1 and 2. The analytical curve in the range 10.0-50.0 mu g/mL (r(2) = 0.999) provided LOD and LOQ for 1 and 2 of 2.1/6.3 and 1.1/3.5 mu g/mL, respectively. The RSD for migration times were 0.12 and 1.0% for peak area ratios with 100.0 +/- 1.4% of recovery. Conclusions - A novel high-performance MEKC method developed for the analysis of butenolides 1 and 2 in leaf extracts of P. malacophyllum allowed their quantitative determined within an analysis time shorter than 5 min and the results indicated CE to be a feasible analytical technique for the quantitative determination of butenolides in Piper extracts. Copyright (C) 2010 John Wiley & Sons, Ltd.

Fabrication of disposable voltammetric electronic tongues by using Prussian Blue films electrodeposited onto CD-R gold surfaces and recognition of milk adulteration

A new approach to fabricate a disposable electronic tongue is reported. The fabrication of the disposable sensor aimed the integration of all electrodes necessary for measurement in the same device. The disposable device was constructed with gold CD-R and copper sheets substrates and the sensing elements were gold, copper and a gold surface modified with a layer of Prussian Blue. The relative standard deviation for signals obtained from 20 different disposable gold and 10 different disposable copper electrodes was below 3.5%. The performance, electrode materials and the capability of the device to differentiate samples were evaluated for taste substances model, milk with different pasteurization processes (homogenized/pasteurized, ultra high temperature (UHT) pasteurized and UHT pasteurized with low fat content) and adulterated with hydrogen peroxide. In all analysed cases, a good separation between different samples was noticed in the score plots obtained from the principal component analysis (PCA). Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Multivariate Analysis for the Classification Differentiation of Brazilian Sugarcane Spirits by Analysis of Organic and Inorganic Compounds

Brazilian sugarcane spirits were analyzed to elucidate similarities and dissimilarities by principal component analysis. Nine aldehydes, six alcohols, and six metal cations were identified and quantified. Isobutanol (LD 202.9 mu gL-1), butiraldehyde (0.08-0.5 mu gL-1), ethanol (39-47% v/v), and copper (371-6068 mu gL-1) showed marked similarities, but the concentration levels of n-butanol (1.6-7.3 mu gL-1), sec-butanol (LD 89 mu gL-1), formaldehyde (0.1-0.74 mu gL-1), valeraldehyde (0.04-0.31 mu gL-1), iron (8.6-139.1 mu gL-1), and magnesium (LD 1149 mu gL-1) exhibited differences from samples.

Volsurf Descriptors to Analyse Anti-HCV and Cytotoxic Activities of Sesquiterpene Lactones from Asteraceae Family

Various significant anti-HCV and cytotoxic sesquiterpene lactones (SLs) have been characterized. In this work, the chemometric tool Principal Component Analysis (PCA) was applied to two sets of SLs and the variance of the biological activity was explored. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. The calculations were performed using VolSurf program. For anti-HCV activity, PC1 (First Principal Component) explained 30.3% and PC2 (Second Principal Component) explained 26.5% of matrix total variance, while for cytotoxic activity, PC1 explained 30.9% and PC2 explained 15.6% of the total variance. The formalism employed generated good exploratory and predictive results and we identified some structural features, for both sets, important to the suitable biological activity and pharmacokinetic profile.

Estrogen receptor: Structural differences and potential implications on selectivity examined by the GRID/CPCA approach

Selective Estrogen Receptor Modulators ( SERMs) have been developed, but the selectivity towards the subtypes ( ER or ER is not well understood. Based on three-dimensional structural properties of ligand binding domains, a model that takes into account this aspect was developed via molecular interaction fields and consensus principal component analysis (GRID/CPCA).

A chemometric study of the 5-HT1A receptor affinities presented by arylpiperazine compounds

Arylpiperazine compounds are promising 5-HT1A receptor ligands that can contribute for accelerating the onset of therapeutic effect of selective serotonin reuptake inhibitors. In the present work, the chemometric methods HCA, PCA, KNN, SIMCA and PLS were employed in order to obtain SAR and QSAR models relating the structures of arylpiperazine compounds to their 5-HT1A receptor affinities. A training set of 52 compounds was used to construct the models and the best ones were obtained with nine topological descriptors. The classification and regression models were externally validated by means of predictions for a test set of 14 compounds and have presented good quality, as verified by the correctness of classifications, in the case of pattern recognition studies, and b, the high correlation coefficients (q(2) = 0.76, r(2) = 0.83) and small prediction errors for the PLS regression. Since the results are in good agreement with previous SAR studies, we can suggest that these findings can help in the search for 5-HT1A receptor ligands that are able to improve antidepressant treatment. (c) 2007 Elsevier Masson SAS. All rights reserved.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

Application of chemometric methods in the evaluation of chemical and spectroscopic data on organic matter from Oxisols in sewage sludge applications

Chemometric methods can contribute to soil research by permitting the extraction of more information from the data. The aim of this work was to use Principal Component Analysis to evaluate data obtained through chemical and spectroscopic methods on the changes in the humification process of soil organic matter from two tropical soils after sewage sludge application. In this case, humic acids extracted from Typic Eutrorthox and Typic Haplorthox soils with and without sewage sludge application for 7 consecutive years were studied. The results obtained for all of the samples and methods showed two clusters: samples extracted from the two soil types. These expected results indicated the textural difference between the two soils was more significant than the differences between treatments (control and sewage sludge application) or between depths. In this case, an individual chemometric treatment was made for each type of soil. It was noted that the characterization of the humic acids extracted from soils with and without sewage sludge application after 7 consecutive years using several methods supplies important results about changes in the humification degree of soil organic matter, These important result obtained by Principal Component Analysis justify further research using these methods to characterize the changes in the humic acids extracted from sewage sludge-amended soils. (C) 2009 Elsevier B.V. All rights reserved.